Our study underscores that DNN-based mortality event classifier offers a novel intelligent approach for forecasting and assessing the prognosis of AHF patients in the ICU. Additionally, the ICU scores stand out as the most predictive features, which implies that in the decision-making process of the models, ICU scores can provide the most crucial information, making the greatest positive or negative contribution to influence the incidence of in-hospital mortality among patients with acute heart failure.
Keyphrases
- acute heart failure
- intensive care unit
- heart failure
- mechanical ventilation
- neural network
- end stage renal disease
- risk factors
- decision making
- ejection fraction
- cardiovascular events
- chronic kidney disease
- newly diagnosed
- prognostic factors
- healthcare
- coronary artery disease
- cardiovascular disease
- patient reported outcomes
- social media